Plug-and-Play Zero-Shot NLP with Sieves

Generative models are dominating the spotlight lately – and rightly so. Their flexibility and zero-shot capabilities make it incredibly fast to prototype NLP applications. However, one-shotting complex NLP problems often isn’t the best long-term strategy.
Introducing Sieves: a lightweight, model-agnostic toolkit for building plug-and-play NLP document processing pipelines. It brings together structured generation, modular components, and practical utilities to help you prototype quickly and scale confidently, without large datasets or fine-tuning.
Whether you’re building information extraction workflows, classification pipelines, or multi-step document processing systems, this tutorial will show you how to do it faster, cleaner, and more reliably.

About the Speaker

I’m a machine learning engineer, these days mostly working in natural language processing. I have soft spots for data visualization, interpretable ML, and the decentralization of AI.
I build NLP systems for a living. Occasionally they work. I don’t believe that attention is all we need. What I do believe in: pragmatism, taking a deep breath before falling for the next hype, and touching grass.

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